MARKETING
If Harry Potter led marketing operations, where would his team sit?
You’ve just graduated from MOpswarts and been declared a marketing ops (MOps) wizard. As you step off the train armed with a wand, sweet robes and cache of spells, you’re ready to help your company thrive with martech magic.
You’re especially jazzed about the AlohoMOpsa spell you found hidden away in the bowels of MOpswarts, which allows you to remake the org structure of any company and move MOps closest to the department where it can best flourish. Should it sit with marketing? Wait, maybe IT? Perhaps sales?
Thinking of your company, you break out your MOpsrauder’s Map, and state, “I solemnly swear I’m trying to help customers,” and the options magically appear with their pros and cons.
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Move MOps closer to marketing
It is marketing operations after all, right? Maybe. Success depends on the CMO. If they see MOps as a trusted advisor and have a solid understanding of martech tools and governance, prepare for raging success. If the opposite is true, consider another department destination.
Goodies: The closer MOps is to the heart of the marketing organization, the higher the MOps marketing IQ and empathy, focusing innovation and energy on what matters most. This enables an agile MOps organization that can power a CMO’s vision. With closer proximity to MOps, marketers are also better sensitized to martech, governance and process. The more marketers know, the more likely they will design programs that work with (and not against) MOps’ strengths.
Gotchas: Like a Ferrari with the wrong driver, a rockstar MOps team with an unreasonable CMO can end in a fiery, Fast and Furious-like explosion. When CMOs thwart governance, ignore process and prioritization and disregard tech constraints, MOps is better situated in an adjoining department to create a protective buffer. Another gotcha to watch out for: if MOps is situated too far from IT, it will be harder to get larger systems integrations or data projects funded and prioritized.
When this works well: When CMOs truly partner with and understand MOps orgs, magic happens. CMOs must also be tight with CIOs, framing the prioritization discussions regarding revenue and ROI to get a seat at the table. If the CIO solves 500k problems, a CMO’s revenue or cost-saving opportunities must exceed that bar to gain traction. Consider funding marketing dedicated resources on the CIO’s team to benefit from IT’s overall tech bench and get marketing prioritized.
Move MOps closer to IT
Being closer to the “big iron” of infrastructure in a company can unlock sophisticated capabilities; it can also result in slower programs or efforts that stray from marketing priorities.
Goodies: MOps teams have better access to IT budgets, prioritization processes and technical firepower, giving larger systems integrations and data projects a higher chance of success. Compared with marketing, IT orgs tend toward more structure and process, making governance easier to enable. The org buffer that being in IT creates is also useful for MOps when CMOs are unreasonable (you know who you are), making sensible pushback possible.
Gotchas: Removed from the marketing team, MOps can lose touch with marketing pain points and stray from the CMO’s vision, resulting in strategic misfires. The sense of urgency can also be lost as the CIO’s shadow shields MOps from the heat of the CMO’s sun – or completely blots it out with other company priorities.
When this works well: When MOps is closer to IT but funded by marketing, you get the best of two worlds: first, IT doesn’t stray from marketing priorities; second, marketing gets the benefit of IT’s technical depth needed for more sophisticated programs. Without budget or another form of authority, marketing is often too low on the IT list of priorities.
Move MOps closer to sales
The closer MOps is to customers, the tighter marketing programs are interwoven with revenue objectives. Go too far, however, and longer-term marketing priorities like brand suffer.
Goodies: Sitting closer to customers will focus MOps like a laser on enabling revenue-producing programs. As MOps participates in sales discussions, marketing gets crisper and more focused to ensure a healthy, high-quality pipeline, as there is little support for anything that doesn’t immediately add value. The heat is also on for better, more consistent sales enablement content to keep sales leaders closing deals rather than creating decks.
Gotchas: Sales’ intense focus on short-term revenue can come at the expense of longer-term growth. Sales orgs may not see or wish to invest in brand or other more esoteric forms of marketing that don’t generate immediate benefits for bearers of quota. While demand gen campaigns provide more tangible fuel for the sales engine, cultivating brand, advocacy or social media presence clears the road for a longer, more profitable journey.
When this works well: Exec leadership must buy into the power of marketing to engage with customers at scale. In-person customer conversations are superior to emails or webinars but far less economical to execute. By casting a wider net, marketing can more economically identify valuable prospects and transition revenue-ready leads to sales.
Which model is the best? No model is perfect, so it depends on your needs. Desire to power a CMOs vision to deliver world-class programs? Marketing could be your best bet. Need sophisticated programs that require deep technical expertise? Proximity to IT will help. Want to ensure sales and marketing work hand in glove? Closer to sales is a good bet.
What if you want the benefits of all three? As RevOps matures, incredible possibilities exist in the harmonized world of sales, marketing and service. But you may have to head back to MOpswarts and find a potion or spell to crack that one.
You close up the MOpsrauder’s Map and whisper, “AlohoMOpsa,” while flicking your wand. With revenue targets and customer delight on your mind, the company’s departments swirl before you, and you make your choice.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
Introduction
With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.
Types of YouTube Ads
Video Ads
- Description: These play before, during, or after a YouTube video on computers or mobile devices.
- Types:
- In-stream ads: Can be skippable or non-skippable.
- Bumper ads: Non-skippable, short ads that play before, during, or after a video.
Display Ads
- Description: These appear in different spots on YouTube and usually use text or static images.
- Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).
Companion Banners
- Description: Appears to the right of the YouTube player on desktop.
- Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.
In-feed Ads
- Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.
Outstream Ads
- Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.
Masthead Ads
- Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.
YouTube Ad Specs by Type
Skippable In-stream Video Ads
- Placement: Before, during, or after a YouTube video.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Action: 15-20 seconds
Non-skippable In-stream Video Ads
- Description: Must be watched completely before the main video.
- Length: 15 seconds (or 20 seconds in certain markets).
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
Bumper Ads
- Length: Maximum 6 seconds.
- File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
- Resolution:
- Horizontal: 640 x 360px
- Vertical: 480 x 360px
In-feed Ads
- Description: Show alongside YouTube content, like search results or the Home feed.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Headline/Description:
- Headline: Up to 2 lines, 40 characters per line
- Description: Up to 2 lines, 35 characters per line
Display Ads
- Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
- Image Size: 300×60 pixels.
- File Type: GIF, JPG, PNG.
- File Size: Max 150KB.
- Max Animation Length: 30 seconds.
Outstream Ads
- Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
- Logo Specs:
- Square: 1:1 (200 x 200px).
- File Type: JPG, GIF, PNG.
- Max Size: 200KB.
Masthead Ads
- Description: High-visibility ads at the top of the YouTube homepage.
- Resolution: 1920 x 1080 or higher.
- File Type: JPG or PNG (without transparency).
Conclusion
YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
A deeper dive into data, personalization and Copilots
Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.
To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.
Dig deeper: Salesforce piles on the Einstein Copilots
Salesforce’s evolving architecture
It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?
“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”
Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”
That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.
“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.
Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”
Let’s learn more about Einstein Copilot
“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.
For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”
Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”
It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”
What’s new about Einstein Personalization
Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?
“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”
Finally, trust
One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.
“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”
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